Arthritis is the leading cause of daily discomforts, the most prevalent chronic condition, and a top rank cause of activity limitations for older people. Interest in older people's quality of life, rather than just its length, is bringing arthritis to the forefront of health gerontology research. This project will study physical and social disability among older U.S. adults with arthritis. It begins with descriptive rates for a wide variety of disability measures (gross mobility, motions and strength, activities of daily living, role and leisure activities, environmental and social needs, and health outlook). Then, how morbidity and sociodemographic factors help predict the presence and levels of disabilities is studied. The morbidity predictors concern the arthritis itself and presence of comorbidities. The sociodemographic predictors are age, sex, race, marital status, and living arrangements. We will see if disability is exacerbated for certain population groups (such as widowed men, elderly (ages 75+) people with no current medical care for their arthritis, elderly people with multiple chronic conditions). The hypothesis that the driving force behind disability is morbidity, more so than sociodemographic (illness response) factors, will be examined. Several special topics will be pursued: (1) Sex differences in arthritis disability, and medical vs. social reasons for them, (2) Comorbidity with arthritis (how other specific chronic conditions overlap with it), and (3) Which disabilities typically occur together among arthritis people. The sensitivity of results to varying scopes of ICD codes for "arthritis" will be checked. The data source is the Supplement on Aging (SOA) which accompanied the 1984 National Health Interview Survey. The SOA has a national probability sample of persons 55+ years old and contains extensive items on self reported chronic conditions and disabilities. The arthritis subsample will have data for over 7000 persons. Technical work will start with estimating arthritis prevalence and disability rates for the U.S. (civilian noninstitutional) population. To test stated hypotheses about predictors of disability, multivariate techniques (logistic and other regressions, loglinear analysis) will be used. The project will complement growing medical information about arthritis with social information about how the disease affects daily living and health outlook of older persons. Based on the findings, health professionals and planners can devise therapies and programs to reduce the most common disabilities among arthritis people and to aid the most disabled social groups.